Francesco Holecz. TUBE II meeting - 17 June Land Degradation. Land Degradation

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Angelina Phillips
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1 Land Degradation Francesco Holecz

2 Objective To identify and monitor land degraded areas, in particular those related to agricultural and pastoral activities. Following products are generated: Land cover map Land cover change map Crop acreage and yield Pastoral extent Digital Elevation Model

3 Team Global Monitoring for Food Security ( consortium TUBE II (a meeting Belgian-Swiss-Italian-German - 17 June 2002 partnership). Users Food and Agriculture Organisation (FAO) - GIEWS Unit World Food Programme - VAM Unit FEWS Net - USGS Regional Early Warning Units SADC AGRHYMET RCMRD National Early Warning Units

4 Methodology HighRes Opt HighRes SAR MedRes Opt MedRes SAR Rule based S-T Decision Classifier Spectral Classes Temporal Changes Baseline Map Rule based Decision Classifier Rule based S-T Decision Classifier Spectral Classes Temporal Changes Local to National Scale - Baseline Map -Products Neural Network based on Area Fraction Images Products National Scale

5 Sensors HighRes ASAR Alternating Polarization ALOS PALSAR Fine Beam Thematic Mapper / ETM+ SPOT-4 MedRes MERIS Full Resolution MODIS 500m ASAR Wide Swath ALOS PALSAR ScanSAR

6 Sites GMFS sites K&C sites

7 Validation - Sampling Design M0709 M0710 M0733 M km 250 m 1 km

8 Processing Chain - SARscape in Arcview and ENVI Environment

9 Processing Chain - SARscape Basic It includes a set of processing steps for the generation of SAR products based on intensity and coherence. This module is complemented by a optical multi-spectral data processing capabilities and a multi-purpose tool. Focusing This module developed by aresys supports the focusing of RADARSAT-1 (FB,SB,SS), ENVISAT ASAR (IM,AP,WS), and ALOS PALSAR data (FB,SS,PM). Gamma & Gaussian Filter This module developed by Privateers includes a whole family of SAR specific filters. They are particularly efficient to reduce speckle, while preserving the radar reflectivity, the textural properties and the spatial resolution, especially in strongly textured SAR images. Interferometry It supports the processing of Interferometric SAR (2-pass interferometry, InSAR) and Differential Interferometric SAR (n-pass interfereometry, DInSAR) data for the generation of Digital Elevation Model, Coherence, and Land Displacement/Deformation maps.

10 Processing Chain - SARscape ScanSAR Interferometry It extends TUBE the II Interferometry meeting - 17 one June to 2002 the ScanSAR mode, offering the capabilities to generate interferograms over large areas (500 x 500 km). This module developed by aresys combined with the Interferometry one enables also the generation of Digital Elevation Model, Coherence, and Land Displacement/Deformation maps. SAR Polarimetry / Polarimetric Interferometry The PolSAR/PolInSAR module supports the processing of polarimetric (ALOS PALSAR, RADARSAT-2, and TerraSAR-X-1) and polarimetric interferometric (ALOS PALSAR) SAR data. Permanent Scatters The Permanent Scatterers module developed in collaboration with aresys enables to determine mm-scale displacements of individual features on the ground.

11 ALOS PALSAR Processing Geocoded sigma naught image JAXA

12 ALOS PALSAR Processing Geocoded flattened interferogram JAXA

13 ALOS PALSAR Processing - Intensity Lake Urban Forest JAXA

14 Coherence - Non-zero Doppler Annotation <γ>=0.1 <γ>=0.27 <γ>=0.16 JAXA

15 Coherence - Zero Doppler Annotation <γ>=0.06 <γ>=0.32 <γ>=0.17 JAXA

16 ALOS PALSAR Processing - Polarimetry JAXA JAXA Pauli Decomposition H/A/α Decomposition

17 SAR-Optical - Ruled based Decision Classifier Optical TUBE Spectral II meeting - 17 June 2002 Classes Optical Spectral- Temporal Classes low med low high med med low Multi-temporal SAR based Classes

18 SAR-Optical - Ruled based Decision Classifier - Example Optical Spectral Classes Multi-temporal temporal SAR data Final Product

Senegal 2006 - Early Warning Product Coherence Mean

19 Senegal Early Warning Product Coherence Mean Intensity Intensity Change ENVISAT ASAR Wide Swath, May-June

Senegal, 2006 - Multi-temporal temporal Mosaic Multi-temporal ENVISAT ASAR Alternating Polarization mosaic with a

20 Senegal, Multi-temporal temporal Mosaic Multi-temporal ENVISAT ASAR Alternating Polarization mosaic with a spatial resolution of 15 metres. Note that the mosaicing procedure is completely automatic. May 2006 July 2006 August 2006

21 Senegal, 2005 Based on ENVISAT ASAR AP and Landsat TM

22 Senegal, 2005 Based on MERIS FR fapar

23 Malawi 2005/06 - Early Warning Product Sept-Oct 2005 Mar-Apr 2006 Coherence Mean Intensity Intensity Change ENVISAT ASAR Wide Swath

24 Malawi 2005/06 Based on ENVISAT ASAR AP and Landsat TM

25 Malawi 2005/06 - Extent of Cultivation + MODIS DMP ASAR WS Intensity

26 Zimbabwe 2006/07 - ENVISAT ASAR AP Planning Continuous acquisitions between October and June

27 Zimbabwe 2006/07 - LCM at country level derived from Landsat TM October - Spectral Classes April - Spectral Classes Thematic Classes

28 The ALOS PALSAR Role Temporal AND spatial resolution are key parameters to monitor vegetation changes. ALOS PALSAR data will be exploited in combination with ENVISAT ASAR AP and Landsat TM data, hence enabling to increase the temporal resolution to complement C-band data (in particular important after the initial vegetation growth) and optical data. The use of long-term L-band coherence (in Image and ScanSAR mode) will provide a significant additional information in land degraded areas.

29 Thank you for your Attention

30 On Earth displacement and ScanSAR. just for Shimada 200 km

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